![](bg5.png)
An alternative way to evaluate the effectiveness
of our method is the re-projection error for all the
images in an image set. Experiments affirmed that
the re-projection error is significant small since it
does not exceed 4 pixels for images of dimensions
2048× 1536.
Through experimentation we have reached the
conclusion that the quality of the results is mainly af-
fected by the selection of the first two views. These
views should correspond to views taken from angles
that are as far apart as possible to capture adequately
the depth of the face. Furthermore, the accuracy of the
feature selection procedure largely affects the accu-
racy of the reconstruction, since the reconstruction al-
gorithm is based on the determination of the epipoles
and hence is very sensitive to measurement noise.
5 CONCLUSIONS
In this paper, we have presented a two-step technique
to deal with the challenging task of face reconstruc-
tion in three dimensions from a set of uncalibrated
images. In the first step of the proposed approach,
15 salient features are manually identified in all the
images of the set and their 3D coordinates are re-
trieved using an uncalibrated 3D reconstruction algo-
rithm. In the second step, a generic face model is de-
formed according to the 3D points produced in the
first step. Since the 3D coordinates of only 15 points
are known, the 3D coordinates for the rest nodes of
the generic model are retrieved through interpolation
and extrapolation, with extra provisions to ensure a
proper face reconstruction. The experimental results
prove that the combination of a robust SfM algorithm
with a generic mesh model deformed using thin plate
smoothing splines can yield very satisfactory 3D re-
constructions.
ACKNOWLEDGEMENTS
This work was supported by the ”SIMILAR” Eu-
ropean Network of Excelence on Multimodal Inter-
faces of the IST Programme of the European Union
(www.similar.cc)
.
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